The consumption of low-dose aspirin (LDA) to prevent cardiovascular disease continues to increase worldwide. Consequently, the number of chronic LDA users seeking dental procedures that require complementary acute anti-inflammatory medication has also grown. Considering the lack of literature evaluating this interaction, we analyzed the gastric and renal effects caused by a selective COX-2 inhi...

Linear Discriminant Analysis (LDA) is among the most optimal dimension reduction methods for classification, which provides a high degree of class separability for numerous applications from science and engineering. However, problems arise with this classical method when one or both of the scatter matrices is singular. Singular scatter matrices are not unusual in many applications, especially f...

Linear discriminant analysis (LDA) is one of the most popular methods of classification. For high-dimensional microarray data classification, due to the small number of samples and large number of features, classical LDA has sub-optimal performance corresponding to the singularity and instability of the within-group covariance matrix. Two modified LDA approaches (MLDA and NLDA) were applied for...

Lithium diisopropylamide (LDA)-mediated ortholithiations of 2-fluoropyridine and 2,6-difluoropyridine in tetrahydrofuran at -78 °C were studied using a combination of IR and NMR spectroscopic and computational methods. Rate studies show that a substrate-assisted deaggregation of LDA dimer occurs parallel to an unprecedented tetramer-based pathway. Standard and competitive isotope effects confir...

Linear discriminant analysis (LDA) is one of the most popular classification algorithms for brain-computer interfaces (BCI). LDA assumes Gaussian distribution of the data, with equal covariance matrices for the concerned classes, however, the assumption is not usually held in actual BCI applications, where the heteroscedastic class distributions are usually observed. This paper proposes an enha...

Singularity problems of scatter matrices in Linear Discriminant Analysis (LDA) are challenging and have obtained attention during the last decade. Linear Discriminant Analysis via QR decomposition (LDA/QR) and Direct Linear Discriminant analysis (DLDA) are two popular algorithms to solve the singularity problem. This paper establishes the equivalent relationship between LDA/QR and DLDA. They ca...

— The effects of magnetism on high pressure properties of transition metals and transition metal compounds can be quite important. In the case of Fe, magnetism is responsible for stability of the body-centered cubic (bcc) phase at ambient conditions, and the large thermal expansivity in face-centered cubic (fcc) iron, and also has large effects on the equation of state and elasticity of hexagon...

The optical properties of ZnO nanowires containing defects are investigated using first-principles densityfunctional theory incorporating the LDA+U formalism. Calculations include defects in the form of substitutional N, Zn, and O vacancies as well as +1 charged O vacancy. Our calculations reveal that the presence of vacancies contribute strongly to optical absorption in the visible. Furthermor...

A comparative analysis of the electronic structure obtained in DFT/LDA and LDA + DMFT approaches possible isostructural analogues iron superconductors InCo 2 As KInCo 4 with parent high-temperature superconductor system BaFe is carried out. It established that spite rather large value electron-electron correlations (local Coulomb interaction on Co- $$3d$$ shell $$U = 4.0$$ eV, Hund exchange $$J...